What is Cyber-Physical System (CPS)?

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Some basic idea about related matter needed to be known to understand what is cyber-physical system (CPS). Among them, one is embedded system, the other is Internet of Things (IoT), the other is Autonomous Car , the other is sensor network. A cyber-physical system (CPS) is a mechanism. That mechanism is designed to be controlled or monitored by computer-based algorithms. The total system obviously integrated with the Internet, hence the cyber part of name. In cyber-physical systems, physical and software components are operating on different spatial, temporal scales. Use cases of CPS include autonomous automobile systems, medical monitoring, process control systems, robotics systems, automatic pilot avionics, smart grid, traffic logistics system and so on.

What is Cyber-Physical System (CPS)?

A cyber-physical system (CPS) refers to the combination of computer-aided, software components with mechanical and electronic parts, which can be accessed via a data infrastructure, such as data centers where the Internet communicates. A cyber-physical system is characterized by its high degree of complexity. The theoretical basis of cyber-physical systems arises from the networking of embedded systems through wired or wireless communication networks. The conceptualization follows the need for a new theoretical basis for the research and development of large, distributed, complex systems.

Mobile cyber physical systems has inherent mobility and is a prominent subcategory of cyber-physical systems.

Unlike traditional embedded systems, a full-fledged CPS is typically designed as a network of elements that interact with physical inputs and outputs instead of isolated devices. The idea is closely linked to the concepts of robotics and sensor networks, which are controlled and supervised by intelligence mechanisms typical of the field of artificial intelligence. The continuous advances in science and engineering will improve the relationship between computational and physical elements that through intelligent mechanisms will dramatically increase the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. This will expand the potential of cyber-physical systems in several dimensions, including: intervention (eg, collision avoidance); precision (eg, robotic surgery and nano-technology manufacturing); operation in dangerous or inaccessible environments (eg, search and rescue, fire fighting, and abyssal sea exploration); coordination (eg, air traffic control, war); efficiency (eg zero-buildings of net energy); and improvement of human capabilities (eg, health monitoring).

Current Challenges Around the Cyber-Physical System (CPS)

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Particularly in the Anglo-American area, theorizing of the term cyber-physical system is promoted. Here, a clear distinction between the term and other trends and development directions of complex information and communication systems is in the foreground. Further academic research focuses on the emerging challenges of system design. Challenges include:

Complexity reduction and development of stabilizing control architectures for cyber-physical systems

Investigations are encouraged to further develop industrial production facilities and production processes. The aim of these activities is to support already intensively computer-aided industries in the introduction and use of widespread network structures for the embedded systems used.

Design of Cyber-Physical System (CPS)

As today there is no common way in design practice which involves all the types of engineering & art disciplines in CPS, concept designing is complex matter. Recently by using co-simulation disciplines go advantage to cooperate without enforcing new design methods.

Designing and deploying a cyber-physical production system can be done based on the 5C architecture – connection, conversion, cyber, cognition, and configuration.

Connection – devices can be designed to self-connect and self-sensing for its behavior.

Conversion – data from self-connected devices and sensors are measuring the features of critical issues with self-aware capabilities, machines can use the self-aware information to self-predict its potential issues.

Cyber – each machine is creating its own “clone” by using these instrumented features and further characterize the machine health pattern some methodology. The established “clone” can perform self-compare for peer-to-peer performance for further synthesis.

Cognition – the outcomes of self-assessment and self-evaluation will be presented to users based on an “infographic” meaning to show the content and context of the potential issues.

Configuration – the machine or production system can be reconfigured based on the priority and risk criteria to achieve resilient performance.